Mühendislik Fakültesi / Faculty of Engineering

Permanent URI for this collectionhttps://hdl.handle.net/11727/1401

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An advanced human error assessment approach: HEART and AV-DEMATEL
(2019) Can, Guelin F.; Delice, Elif K.
Human error assessment and reduction technique (HEART) is one of the most commonly used human error assessment approaches which computes human error probability (HEP) to prioritize errors related to human actions. HEART is a powerful tool considering error producing conditions (EPCs) which increase the HEP for generalized task versions named as generic task types (GTTs). HEART can give a solution including prevention of human-related errors (HREs) and reduction of the HREs' impacts via implementing additional controls. However, it has many shortcomings for real-life error assessments. In this context, this study aims to improve effective usage of HEART through an advanced version of decision-making trial and evaluation laboratory (AV-DEMATEL). The reason to perform AV-DEMATEL is to show the complex effect relations between main tasks (MTs), subtasks (STs), and EPCs in a process. For this aim, an integrated effect relation matrix is proposed for DEMATEL and importance weights of MTs, STs, and EPCs are computed based on this matrix. In addition, not only HREs are considered but also machine-related errors (MREs) are taken into account to make error assessment for the process. The proposed approach also provides flexibility to categorize STs in different GTTs. Finally, a new term "process error probability" including HREs' probabilities and MREs' probabilities is recommended to compute error probability in an integrated manner for the process. To utilize the proposed approach, an example of a steam boiler daily control process is given.
An Advanced Stochastic Risk Assessment Approach Proposal Based on KEMIRA-M, QFD and Fine-Kinney Hybridization
(2021) Can, Gulin Feryal; Toktas, Pelin
In this study, an advanced stochastic risk assessment approach based on integration of advanced version of quality function deployment (AV-QFD) and Modified Kemeny Median Indicator Rank Accordance (KEMIRA-M) is proposed. It is aimed to perform a new criterion weighting procedure based on four different distributions as uniform, symmetric triangular, left asymmetric triangular, right asymmetric triangular distributions. The AV-QFD includes correlations between criteria (top roof of QFD), risk degrees (RDs) of risk types (RTs) (customer needs part of QFD), correlations between RTs and criteria sets (CSs) (in the middle of QFD) to obtain the criteria priorities. Correlations on the top roof of QFD comprises three types: correlations between criteria in the first CS, correlations between criteria in the second CS and correlations between criteria in both CSs. Additionally, Fine-Kinney method is performed in AV-QFD to compute RDs of RTs in the customer needs part. Then for each expert, the correlation-based importance degree (CBID) of each criterion is obtained to rank criteria for each CS. MATLAB code was performed to see the effect of different trial numbers and replications on risk assessment. It was observed that although uniform distribution provides the best value, the same alternative ranking was obtained for all distributions. In addition, right asymmetric triangular distribution converged to the best value rapidly in practice made in this study.
Ag-Carried CMC/Functional Copolymer/ODA-Mt Wled-Treated NC And Their Responses to Brain Cancer Cells
(2018) Rzayev, Zakir M. O.; Bunyatova, Ulviye; Lovell, Jonathan F.; Shen, Weipeng; Thomay, Tim; Cartwright, Alexander; 0000-0002-9705-1722; 30184772; J-5194-2019
The subject of this work is synthesis and characterization of novel multifunctional nanocomposite (8/2A-NC) consisting (1) carboxymethyl cellulose (CMC) as a matrix biopolymer and poly (maleic acid-tilt-acrylic acid) as a reactive synthetic partner matrix polymer; (2) octadecyl amine montmorillonite (ODA-MMT) reactive organoclay provide intercalated silicate layers structures and aqueous colloidal dispersing medium, and MMT as carriers and targeting agents for anticancer agents in drug delivery systems, respectively. ODA as a intercalated surfactant finely dispersed 8/2A NC and its compatibility with matrix polymers via the interfacial polarization (complexing) and functionalization of matrix polymers by amine (ODA) and carboxylic acids from both the CMC and copolymer; (3) silver nanoparticles (AgNPs) as in-situ generated onto matrix polymers with unique nano-size and morphology parameters was synthesized. Important material science and bioengineering aspects of these investigations included (a) novel approach in synthetic pathways; (b) effects of physical and chemical structural rearrangements; (c) effects of Light Emitting Dioda (LED)-treatment on the FT-IR spectra, XRD reflection parameters, SEM-TEM morphology and nano-size and diameter distribution of AgNPs onto matrix polymers; (d) positive effect of LED-treatment of 8/2A nanocomposite and its response to the MIAPaCa-2 and U87 human brain cancer cell lines were evaluated. Novel 8/2A-NC multifunctional drug consisting unique positive, intercalating and encapsulated core-shell morphology structures, nano-size (5.6 run) and narrow diameter distribution (94%) of AgNPs onto matrix polymers [silver NPs (0.25%) in 8/2A NC (25%)] with highest volume of contact area compared with used cancer micro-cells show lowest cell viability as an excellent anticancer platform. 8/2A-NC is a novel multifunctional drug with intercalating and encapsulated core-shell morphology structures consisting of positively charged, non-randomly distributed AgNPs with a large contact area and low diameters (5-6 nm). The anticancer properties of (This factor is not conformed experimentally in work) this drug can be explained by the following structural factors: 8/2A-NC contains a combination of active sites from protonated hydroxyl, carboxyl and amine groups; Ag + -cations and ODA-MMT with high physical and chemical surface areas. We suggest this material be further explored for anti-cancer testing.
Airfoil-slat arrangement model design for wind turbines in fuzzy environment
(2020) Atalay, Kumru Didem; Dengiz, Berna; Yavuz, Tahir; Koc, Emre; Ic, Yusuf Tansel
In this study, a multi-element wind turbine blade that consists of NACA 6411 and NACA 4412 leading-edge slat design is investigated computationally. Optimum design parameters of the slatted wind turbine blade leading to maximum value of C-L/C-D related to the turbine power are obtained. In the optimization process, a new fuzzy logic linear programming methodology integrating with fuzzy linear regression and 2D CFD analysis is proposed. The aerodynamic characteristics of the slatted blade are computed by using Incompressible Navier-Stokes equations and k-omega turbulence modeling. Results are compared with the results of linear programming method and direct search optimization method. The computational results reveal that the proposed methodology for performance optimization is more effective than other methods to obtain high-performance value of the C-L/C-D. The maximum value of the C-L/C-D is obtained as 25.1 leading the maximum efficiency of 0.52.
Aligned Polyvinylpyrrolidone Nanofibers with Advanced Electrospinning for Biomedical Applications
(2018) Karayegen, Gokay; Kocum, I. Cengiz; Serdaroglu, Dilek Cokeliler; Dogan, Mustafa; 0000-0001-5215-8887; 30400080; I-4296-2019
BACKGROUND: Electrospinning is a highly effective method in order to generate nano-scaled fibers. In conventional electrospinning technique, geometry of nanofibers are mostly random due to the chaotic behavior of polymer jet. OBJECTIVE: Purpose of this study is to produce aligned nanofibers from PVP polymers with advanced electrospinning technique in order to be used in a potential novel sensor applications, tissue regeneration and engineering. METHODS: In this study, by using finite hollow cylinder focusing electrodes, an external electrostatic field is created. With these electrodes, it is aimed to decrease whipping instability of polymer jet. In addition, it is also investigated that the alignment ratio of nanofibers by using conductive parallel electrodes which placed through jet trajectory. RESULTS: In conclusion, with the effect of electrical field created by cylinder electrodes, radius of the fiber dispersion on the collector was able to be reduced and aligned nanofibers were successfully produced by using electrical field generated from the parallel plates. CONCLUSIONS: Radius of the fiber dispersion on the collector is 9.95 mm and fiber diameters varied between 800 nm and 3 mu m. Additionally, alignment ratio of the fibers is determined with ImageJ software. These alignment of nanofibers can be used in tissue engineering applications and sensor applications.
An Alternative Electrospinning Approach With Varying Electric Field for 2-D-Aligned Nanofibers
(2014) Karatay, Okan; Dogan, Mustafa; Uyar, Tansel; Cokeliler, Dilek; Kocum, Ismail Cengiz; U-7861-2018
In the electrospinning process, unstructured nanofiber mats are produced by oriented fluid jets with an external electrostatic field. Electrospun fibers have wide applications for the fabrication of composite materials, tissue scaffold, and membranes. However, electrospun fiber production systems have many problems, e. g., the bending instability due to the complicated oscillations of polymer jet. In this research, parallel plate and hollow cylindrical conducting electrodes are implemented through the jet trajectory in order to investigate the possibility of controlled deposition of polymer fibers. Parallel electrodes with proper driving sources can generate the steering field for the nanofiber formation at the collector plate based on analog addressing electronics. It was shown that the modulated electric field applied through the parallel plate electrodes notably increased the deposition of the electrospun polymer fibers in a controlled fashion at the collector, which is coherent to the computer simulations. Furthermore, the finite-length hollow cylinder dampened the bending instabilities of the polymer jet which decreases the characteristic spot size of the deposited electrospun fiber to a smaller diameter.
Analysis of Deep Neural Network Models for Acoustic Scene Classification
(2019) Basbug, Ahmet Melih; Sert, Mustafa
Acoustic Scene Classification is one of the active fields of both audio signal processing and machine learning communities. Due to the uncontrolled environment characteristics and the multiple diversity of environmental sounds, the classification of acoustic environment recordings by computer systems is a challenging task. In this study, the performance of deep learning algorithms on acoustic scene classification problem which includes continuous information in sound events are analyzed. For this purpose, the success of the AlexNet and the VGGish based 4- and 8-layered convolutional neural networks utilizing long-short-term memory recurrent neural network (LSTM-RNN) and Gated Recurrent Unit Recurrent Neural Network (GRU-RNN) architectures have been analyzed for this classification task. In this direction, we adapt the LSTM-RNN and the GRU-RNN models with the 4- and 8-layared CNN architectures for the classification. Our experimental results show that 4-layered CNN with GRU structure improve the accuracy.
Analysis of post-graduate theses in Industrial Engineering area of Turkish Universities
(2020) Cetinkaya, Cihan; Uslu, Aysenur; Ozceylan, Eren; Hayirsoz, Kaan Mert
Today, engineers make efforts for post-graduate programs far more than before. The main reasons can be increasing awareness of firms about education, decreasing job opportunities for undergraduate degrees, the increasing demand for being an academician or scholarship opportunities by government. Some firms want their postgraduate student engineers to solve the firm's problems in their master or doctoral thesis as case studies. In this regard industrial engineering is a field that adjusts almost with every sector because of its multidisciplinary nature. Thus, there are many post-graduate theses written in this area. The aim of this paper is to analyze 2,122 postgraduate theses (master & doctoral) which are carried out in the department of industrial engineering in Turkish universities. The data is obtained from the website of Council of Higher Education of Turkey. The time period is determined as 2010-2017 and only the 1780 "permission" theses are analyzed in order to reach keywords for solution approaches and keywords analysis. Nine different indicators are used to analyze the thesis such as; university status, page numbers, language, keywords etc. As a result, this study shows how the theses are clustered according to different indicators and which topics are studied more frequently in recent years. The inference of the paper is important because the results give an insight about the road map of industrial engineering thesis completed in 56 different Turkish universities.
Analysis of the effect of the number of criteria and alternatives on the ranking results in applications of the multi criteria decision making approaches in machining center selection problems
(2020) Ic, Yusuf Tansel; Yurdakul, Mustafa
Multi criteria machining center selection models are widely used in the literature. In the applications of multi-criteria decision making models, machining center selection criteria are directly taken from catalogues. It is known that to have a ranking model sensitive to the weights of the selection criteria, it is especially important to limit the number of selection criteria to 7 +/- 2. A similar proposal can be put forward for the number of machining centers. In this study, whether or not reducing the number of criteria and alternative machining centers make the ranking results more sensitive to the changes in the criteria weights is studied using Spearman's rank correlation test. The study results show that the ranking results become more sensitive with a reduced number of criteria and alternative machining centers.
Analysis of the manufacturing flexibility parameters with effective performance metrics: a new interactive approach based on modified TOPSIS-Taguchi method
(2022) Ic, Yusuf Tansel; Sasmaz, Turgut; Yurdakul, Mustafa; Dengiz, Berna; 0000-0001-9274-7467; AGE-3003-2022
Flexibility is one of the most important strategy parameters to achieve a long-term successful performance for a manufacturing company. Studies in the literature aim to operate a manufacturing system at optimum levels of flexibility parameters under its own manufacturing environment. This study aims to present an interactive analysis framework based on TOPSIS and Taguchi parameter design principles for investigating the effects of different levels of flexibility parameters on the performance of a flexible manufacturing cell (FMC). The main performance metric used in this study is manufacturing lead time. Other important metrics to evaluate quality control and inspection policies are also investigated in this study. To conclude, a combined model of an interactive approach based on TOPSIS and Taguchi methods are used to assess the effectiveness of the flexibility parameters for a FMC.
Analysis of The Performance of A Solar Air Heater With Different Configurations: Effect of Fins And Turbulators
(2022) Erol, Ozgur
Solar air heaters are simple tools used to harvest the energy of the sun. The main objective of the solar air heater design is to get the highest thermal energy from the sun. In order to do this different kinds of fins and turbulators are placed in the flow channel of the solar air heater, which also affects the flow characteristic of the working fluid. In this study, the performance of two different configurations, a turbulator placed at the bottom of the channel and a longitudinal rectangular fin placed on the absorber plate, are investigated using different performance parameters. These parameters are the thermal efficiency, rational exergy management method (REMM) efficiency, flow work, and the temperature distribution on the absorber plate. According to the results, both of the test cases have nearly the same performance, which is higher than the flat solar air except the flow work. When the heat gain per unit flow work is investigated, it can be said that turbulator configuration is the best choice among the configurations that are investigated.
Analysis of the Robustness of the Operational Performance Using a Combined Model of the Design of Experiment and Goal Programming Approaches for a Flexible Manufacturing Cell
(2023) Ic, Yusuf Tansel; Yurdakul, Mustafa; Dengiz, Berna; Sasmaz, Turgut
A combined model of a 2(k) design of experiment (DOE) and goal programming (GP) approaches is presented to determine optimum levels of input variables and analyze their robustness for a multiobjective performance of a flexible manufacturing cell (FMC) in this study. Two main performance metrics, namely, manufacturing lead time (MLT) and surface roughness (SR), are considered performance outputs for the FMC. Machine sequence, robot speed, tool type, and material type are selected as the four input variables on the input side of the proposed model. The study shows that even with a limited number of experiments, one can determine optimum input levels for the multiobjective performance of the FMC and determine their robustness.
Antenna-Type Radiofrequency Generator in Nanoparticle-Mediated Hyperthermia
(2016) Nasseri, B.; Yilmaz, M.; Turk, M.; Kocum, I. C.; Piskin, E.
Induction of hyperthermia using nanoparticles with specific magnetic, electrical, acoustic, optical or thermal properties is a potential alternative to conventional thermal ablation in cancer therapy. In this study, for the first time we employed an antenna-type radiofrequency (RF) generator as the energy source and as a proof of concept the effects of nanoparticles of varying structures and sizes, such as super-paramagnetic iron oxide nanoparticles (SPIONs), gold-coated superparamagnetic iron oxide nanoparticles (Au@SPIONs), spherical gold nanoparticles (AuNPs), and gold nanorods (AuNRs) on RF hyperthermia were examined to determine hyperthermia efficiency of the antenna-type RF generator. In preliminary experiments, RF was applied at varying powers to various nanoparticle solutions. In all cases, temperature rises due to exposure of RF radiation to nanoparticles were captured by using an infrared thermal camera. This procedure was applied to in vitro tests of fibroblast (L-929) and breast cancer (MCF-7) cell lines. Cell viability, apoptosis and necrosis were evaluated in both cell lines to comprehensively determine cell toxicity. Due to their particle size and chemical nature, SPIONs, in the case of highest RF power and nanoparticle concentration, resulted in the lowest cell viability and highest levels of apoptosis and necrosis.
Antibody Immobilization Techniques in Mass Sensitive Immunosensor: Enhanced Sensitivity through Limited Mass Load
(2022) Kirali, Kubra; Brimo, Nura; Serdaroglu, Dilek Cokeliler; https://orcid.org/0000-0002-3053-2169; https://orcid.org/0000-0002-9604-263X; https://orcid.org/0000-0001-8645-9047
Background: Biosensors are analytical devices that include a sample-delivery approach between a biological recognition element and a transducer required to convert the physicochemical change produced from the interaction of biological molecule-receptor interaction into a signal. The immunosensor is a special type of biosensor that includes an antibody as a biorecognition element to detect analytes as antigens. In mass sensitive sensors, antigen-antibody interactions can be specified by measuring the frequency change and the most commonly knowns are the surface acoustic wave, bulk acoustic wave, quartz crystal microbalance and microcantilevers. Methods: Different methods for antibody immobilization, including functionalization of the transducer surface with specific groups, have been reported for antibody immobilization. This stage affects the limit of detection and overall performance. In this review, perspectives on immobilization strategies of mass sensitive immunosensors according to transducer types will be presented. The choice of immobilization methods and their impact on performance in terms of capture molecule loading, orientation and signal improvement will also be discussed. Results: One of the most critical points during the configuration of the biorecognition layer is to improve the sensitivity. Therefore, we initially focused on comparisons of the antibody immobilization strategies in the biorecognition layer in terms of mass load level and high sensitivity. Conclusion: The lack of significant data on the mass accumulations up to the functionalization and antibody immobilization steps, which are the basis of immusensor production, has been identified. However, mass sensitive immunosensors have the potential to become more common and effective analytical devices for many application areas.
Approximation by statistical convergence with respect to power series methods
(2022) Bayram, Nilay Sahin; Yildiz, Sevda
In the present work, using statistical convergence with respect to power series methods, we obtain various Korovkin-type approximation theorems for linear operators defined on derivatives of functions. Then we give an example satisfying our approximation theorem. We study certain rate of convergence related to this method. In the final section we summarize these results to emphasize the importance of the study.
Approximation Properties of King Type -Bernstein Operators
(2019) Dalmanoglu, Ozge; Orkcu, Mediha
The present paper deals mainly with a King type modification of -Bernstein operators. By improving the conditions given in Mursaleen et al. (On (p, q)-analogue of Bernstein operators. Appl Math Comput 266:874-882, 2015a), we investigate the Korovkin type approximation of both -Bernstein and King type -Bernstein operators. We also prove that the error estimation of King type of the operator is better than that of the classical one whenever 0 <= x <= 1/3.
Are Preformed Cooper Pairs The Cause For The Pseudogap in Superconductors?
(2014) Mamedov, T. A.; de Llano, M.; JFS-2792-2023
A weak-coupling scenario wherein bosonic preformed electron pairs emerge upon cooling from two-electron correlations can explain the pseudogap phase consisting of segments where a Bogoliubov-like energy-momentum relation gapped spectrum alternates with a normal ungapped one. Bose-Einstein condensation (BEC) of preformed pairs interacting with the background fermions leads to either [GRAPHICS] - or [GRAPHICS] -wave-like superconducting gaps, the result being sensitive to the magnitude of the total number density of pairs [GRAPHICS] at which BEC occurs and becomes possible already for a moderately anisotropic [GRAPHICS] -wave pairing of fermions repelling each other via isotropic coulombic forces. The present model is compatible with the coexistence of pseudogap and of superconductivity phenomena.
Astrophysical flows near f (T) gravity black holes
(2016) Ahmed, Ayyesha K.; Azreg-Ainou, Mustapha; Bahamonde, Sebastian; Capozziello, Salvatore; Jamil, Mubasher; 27257404
In this paper, we study the accretion process for fluids flowing near a black hole in the context of f (T) teleparallel gravity. Specifically, by performing a dynamical analysis by a Hamiltonian system, we are able to find the sonic points. After that, we consider different isothermal test fluids in order to study the accretion process when they are falling onto the black hole. We find that these flows can be classified according to the equation of state and the black hole features. Results are compared in f (T) and f (R) gravity.
Audio Captioning with Composition of Acoustic and Semantic Information
(2021) Eren, Aysegul Ozkaya; Sert, Mustafa
Generating audio captions is a new research area that combines audio and natural language processing to create meaningful textual descriptions for audio clips. To address this problem, previous studies mostly use the encoder-decoder-based models without considering semantic information. To fill this gap, we present a novel encoder-decoder architecture using bi-directional Gated Recurrent Units (BiGRU) with audio and semantic embeddings. We extract semantic embedding by obtaining subjects and verbs from the audio clip captions and combine these embedding with audio embedding to feed the BiGRU-based encoder-decoder model. To enable semantic embeddings for the test audios, we introduce a Multilayer Perceptron classifier to predict the semantic embeddings of those clips. We also present exhaustive experiments to show the effciency of different features and datasets for our proposed model the audio captioning task. To extract audio features, we use the log Mel energy features, VGGish embeddings, and a pretrained audio neural network (PANN) embeddings. Extensive experiments on two audio captioning datasets Clotho and AudioCaps show that our proposed model outperforms state-of-the-art audio captioning models across different evaluation metrics and using the semantic information improves the captioning performance.
Automated Extraction of Photorealistic Facade Textures from Single Ground-Level Building Images
(2014) Sumer, Emre; Turker, Mustafa; AGA-5711-2022
An integrated approach is presented for the automatic extraction of photorealistic facade textures from single street-level building images. The initial facade texture is extracted using Watershed segmentation. The seed pixels (markers) to trigger the segmentation are located automatically both for the foreground (facade) and the background regions, and the segmentation is carried out repetitively until the facade texture is extracted. The extracted facade image is geometrically rectified using a developed automatic technique based on Hough transformation and interest point detection. The occluded areas on facade textures are restored by employing an image matching-based procedure. The approach was tested on two different datasets captured from the residential areas of Ankara, the capital of Turkey. The datasets contain a total of 40 building facade images that were taken from the street-level. The results indicate that the facade textures are extracted adequately. For facade image extraction, an average quantitative accuracy of 83% was achieved. For rectification, 24 out of 40 buildings provided the positional error under 10 pixels at 95% confidence level. The subjective assessment of facade restoration yielded the mean rating value of 2.46 for the datasets used, in which the rating values are ranked between 1 for "Excellent" and 6 for "Unusable".